in a least-squares sense, where \(\mathbf {y}\)  is a vector collecting all the
first-principles data, and \(\Phi \)  is the so-called design matrix containing
the \(K(\mathbf {x}_i,\mathbf {x}_{b})\)  components and the derivatives with respect
to atomic coordinates and lattice vectors. When fitting simultaneously energies,
forces and stress tensors, as done here, it is expedient to rescale these
quantities by their respective standard deviations [1]}. To
increase the accuracy of the MLFF, it is also possible to tune the relative
importance of energies, forces and stresses during the fitting.
